AI RCoE Opens Doors to Tools, Expertise, and Collaborative Potential

The Arizona Institute for AI and Society (AI²S) with the Office of Responsible AI (ORAI) launched the Artificial Intelligence (AI) Research Communities of Excellence (RCoE) to bring University of Arizona researchers across various departments into shared spaces around broad topic areas that encourage exchange, early concept development, and trans-disciplinary / convergent collaboration that will lead to solidify convergent areas of excellence, the preparation of strong proposals that attract external support, and national leadership. The integration of artificial intelligence and data science is facilitated by faculty experts, as well as AI2S staff scientists. Each community creates an environment where technical and domain experts connect to enhance their research portfolios, as well as build collaborations and contribute to interdisciplinary and convergent projects that support the university’s broader research agenda.

Faculty researchers are encouraged to become part of one or several AI-RCoEs of interest as members, thereby receiving news about upcoming events, participating in building a strong community, and connecting to resources available through AI2S, ORAI, and Research Development Services. RCoEs are forming around existing faculty connections, as well as supporting the university’s strategic research priorities set by the Office of Research and Partnerships. These priorities include AI driven advances in health care, progress toward fusion energy, new approaches to sustainable mining and critical minerals, and an expanded focus on space and national security.

RCoEs operate as bridges that allow individuals with different expertise to understand one another and move ideas forward. David Moore, professor in the School of Natural Resources and the Environment, explains the value of these shared spaces. Moore says, “I think it is really just finding a common space and a common language to communicate, across some disciplines, and having some facilitators in there who are able to speak both languages to a certain point, from a certain point of view.”

Faculty, research staff, and post doctoral scholars may join an RCoE. Once enrolled, members receive notices about upcoming events and are expected to attend at least one activity each semester. Activities include overview sessions, focused pairing meetings, and workshops that guide teams from early ideas to clear proposal concepts.

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Membership opens access to shared data resources, high performance computers, and validated algorithms without separate approval requests. When a group considers a complex problem, new perspectives often surface that may otherwise remain unseen. Ravi Tandon, professor of Electrical and Computer Engineering, notes that the communities do not replace existing departments; rather, the communities amplify the work already in progress by providing a structured forum for collaboration. He adds: “Given this very broad base of expertise that we have in the ECE department and College of Engineering more broadly, I think we are in a very good position to support campus-wide AI efforts. That is how I see the ECE community of excellence.”

All RCoEs have at least one short overview session each year. During this session, the RCoE is defined and participants provide quick introductions to jumpstart networking. RCoEs can connect with the AI Info Series sessions where people can learn more about AI generally, such as which AI tools, data sets, and support staff are available on campus. RCoEs also host networking meetings that may identify a set of funding opportunities or a specific challenge and host researchers that build potential future collaborations. Exercises are provided such that each participant produces an outline for a  one page summary. Staff then review the outline and provide feedback and strategize next steps, thereby reducing in the project funding cycle and preserving momentum.

To see RCoE events, visit the ORAI news and activities site. A selected list of upcoming sessions highlight the range of opportunities within the Communities of Excellence:

• AI + AZ REMADE: Networking and Ideation — March 4; interdisciplinary connections for renewable energy and advanced materials, with formation of teams and expansion of early concepts.
• Trustworthy AI: Networking Session — March 25; a connection forum for researchers who focus on privacy, security, robustness, and governance within trustworthy AI.
• AI + AZ REMADE: One Page Proposal Pitch Session — April 1; participants refine a concise one page concept to support collaboration and position their work for upcoming funding calls.

The AI Research Communities of Excellence offers structure, expertise, and support that help transform interdisciplinary curiosity into meaningful results.  Any U of A faculty, research staff, or post-doctoral researcher who wishes to attend a session can register from the ORAI events site or join a community through this membership form.